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A robotic wheelchair system was designed to assist disabled people with disabilities to walk.

An anticipated sharing control strategy based on topological map is proposed in this paper, which is used to assist robotic wheelchairs to realize interactive navigation. Then, a robotic wheelchair navigation control system based on the brain-computer interface and topological map was designed and implemented.

In the field of robotic wheelchairs, the problems of poor use, narrow application range and low humanization are still not improved.

In the system, the topological map construction is not restricted by the environment structure, which helps to expand the scope of application; the shared control system can predict the users’ intention and replace the users’ decision to realize human-machine interactive navigation, which has higher security, robustness and comfort.

The purpose of this paper is to study the unit train make-up scheme for loaded direction in the heavy haul railway.

A 0-1 nonlinear integer programming model with the aim of minimizing the idling period between actual train arrival time and expected train arrival time for all loaded unit trains are proposed.

The proposed model is applied into a case study based on Daqin heavy haul railway. Results show that the proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

The proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

The purpose of this paper is to realize scientific reasoning and prediction in economic catastrophe, which occurs in the short‐term and leads to invalidation of most classical prediction models through lacking basic sample data.

Based on functional theory, grey number algebra theory, Bayesian network theory and interval grey number theory, the authors established GFAM (1,1), which is grey function analysis model (1,1), to excavate and utilize the existing data sufficiently.

This paper proved least squares parameters theorem and prediction theorem and the process of GFAM (1,1). A case was established and demonstrated the utility and good prediction of this model.

This paper established GFAM (1,1), which overcomes the hysteretic defect of classical prediction model and provides a preferable solution in system prediction in economic catastrophe.

During the coronavirus disease 2019 (COVID-19) pandemic, ubiquitous social media has become a primary channel for information dissemination, social interactions and recreational activities. However, it remains unclear how social media usage influences nonpharmaceutical preventive behavior of individuals in response to the pandemic. This paper aims to explore the impacts of social media on COVID-19 preventive behaviors based on the theoretical lens of empowerment.

In this paper, survey data has been collected from 739 social media users in China to conduct structural equation modeling (SEM) analysis.

The results indicate that social media empowers individuals in terms of knowledge seeking, knowledge sharing, socializing and entertainment to promote preventive behaviors at the individual level by increasing each person's perception of collective efficacy and social cohesion. Meanwhile, social cohesion negatively impacts the relationship between collective efficacy and individual preventive behavior.

This study provides insights regarding the role of social media in crisis response and examines the role of collective beliefs in the influencing mechanism of social media. The results presented herein can be used to guide government agencies seeking to control the COVID-19 pandemic.

Online dating services have been growing rapidly in recent years. However, adopting these services may involve high risk and trust issues among potential users toward both online dating services and the daters they introduce to users. The purpose of this paper is to investigate how perceived benefits vs risks, and trust vs distrust affect user adoption vs non-adoption intentions toward using this rather controversial information and communications technology in the context of online dating.

Structural equation modeling was used to evaluate the research model using data from a survey of 451 single individuals.

The results indicated that perceived benefits play more essential roles in adoption, while perceived risks affect non-adoption more. Individuals' trust in online dating service predicts a major portion of the variation in user benefit perceptions, while distrust in online dating service and in daters that users might select significantly influence perceived risks. Moreover, benefit and risk perceptions can mediate the impacts of trust and distrust on both adoption and non-adoption decisions.

This study extends theories of decision-making in the use of controversial information technologies such as in the case of online dating. It investigates the coexistence of various trust and distrust beliefs as well as benefit and risk perceptions, and their different impacts on adoption and non-adoption in online dating services.

After information systems (IS) implementation, many organizations report that system underutilization causes the failure to meet expected IS investment returns. It is imperative to understand the way to leverage employees’ fullest potential in the IS usage. The paper aims to discuss these issues.

Anchoring on absorptive capacity (ACAP) theory, the authors develop an employee innovation model. Using survey data and structural equation modeling, this research investigates how perceived organizational levers affect innovation with IS usage (INVU) by introducing individual ACAP as a mediator.

The authors find general support for the research model through a survey of 205 employees using SAP business intelligence systems in China. The empirical data shows that three interrelated components of individual ACAP significantly contribute to INVU. The findings also suggest that, both fairness of reward and job autonomy are key organizational levers for the utility of individual ACAP. Furthermore, their effects on INVU can be fully mediated by individual ACAP.

The authors empirically unpack and validate individual ACAP in IS innovation situation. The findings provide academics and practitioners with an understanding of how management can inspire employees’ potential in implemented system innovation.

Social commerce (s-commerce) has gained widespread popularity as a social platform where customers engage in resource-sharing activities such as information exchange, advice-seeking and expressing their opinions on mutual interests. However, existing studies have not fully comprehended the drivers of electronic customer-to-customer interaction (eCCI) and how such behavior contributes to the customer “stick” on s-commerce sites. This study develops the Motivation–Opportunity–Ability (MOA) theory and investigates the impact of MOA factors on eCCI, which in turn affects customer stickiness.

A survey was used to acquire data from 455 valid respondents, and the research employed a combination of fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling.

The results revealed associations between perceived self-efficacy, intrinsic motivation, tie strength with other customers, eCCI and customer stickiness.

Considering the limited availability of complete eCCI frameworks in existing scholarly works, the authors present valuable perspectives on the role of consumer characteristics as both antecedents and consequences of eCCI. Additionally, this study proposes a research agenda for the field of eCCI on s-commerce sites.

The purpose of this paper is to examine the impact mechanism of organizational culture (OC) on Enterprise Resource Planning (ERP) user’s explicit and tacit knowledge-sharing behavior in the context of enterprise systems usage.

Drawing from social cognitive theory, the authors developed a comprehensive model that integrates OC, computer self-efficacy and employees’ knowledge-sharing behaviors. In total, 343 valid questionnaires were collected from ERP users of 115 firms and structural equation modeling technique was used to test the model.

Empirical results suggest that hierarchical culture that focusses on efficacy and uniformity is positively related with employees’ explicit knowledge sharing; group culture that focusses on trust and belonging is positively related with employees’ tacit knowledge sharing, and their relationship is fully mediated by employees’ computer self-efficacy. In addition, computer self-efficacy also partially mediates the relationship between rational culture and employees’ knowledge sharing.

This study provides guidelines for top managers to enhance employees’ computer self-efficacy and facilitate employees’ knowledge-sharing behavior by developing appropriate type of OC.

This study unpacks the mediating mechanism between OC and knowledge sharing, and contributes to the academic research of knowledge management in the context of enterprise systems assimilation.

The purpose of this paper is to examine the impact of chief information officer’s (CIO’s) strategic knowledge and structural power on enterprise systems (ES) success in the context of systems usage.

Drawing upon knowledge-based view, this study links CIO’s strategic knowledge, structural power, ES assimilation and firm performance in an integral model. Sample data were collected in China and partial least squares technique was used to test the model.

Empirical results suggest that CIO’s strategic information technology (IT) knowledge, strategic business knowledge and structural power have significant influence on ES assimilation. While ES assimilation mediates the association between CIO’s strategic knowledge, CIO’s structural power and firm performance. Another interesting finding in the study is that the imbalance of CIO’s strategic business knowledge and strategic IT knowledge is negatively associated with ES assimilation.

This study enriches the extant literatures in IS leadership by showing the significant role of CIO’s knowledge balance and authority in promoting the assimilation of ES within the organization. The empirical findings can provide guidelines for the top executive to select a person who is familiar with both strategic business and IT knowledge to take charge of ES, also, to provide the person with appropriate structural power, in order to achieve the benefits of ES successfully.

Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional software cost estimation methods face the challenge of poor and uncertain inputs.

Under such circumstances, different cost estimation methods vary greatly on estimation accuracy and effectiveness. Therefore, it is crucial to perform evaluation and selection on estimation methods against a poor information database. This paper presents a grey rough set model by introducing grey system theory into rough set based analysis, aiming for a better choice of software cost estimation method on accuracy and effectiveness.

The results are very encouraging in the sense of comparison among four machine learning techniques and thus indicate it an effective approach to evaluate software cost estimation method where insufficient information is provided.

Based on the grey rough set model, the decision targets can be classified approximately. Furthermore, the grey of information and the limitation of cognition can be overcome during the use of the grey rough interval correlation cluster method.

This paper proposed the grey rough set model combining grey system theory with rough set for software cost estimation method evaluation and selection.